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Evaluation of Analytes Characterized with Potential Protective Action after Rat Exposure to Lead
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublikacjaThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Starch-grafted-N-vinylformamide copolymers manufactured by reactive extrusion: synthesis and characterization
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Unsteady aerodynamic forces acting on the rotor blades in the turbine stagewith steam extraction.
PublikacjaPrzeprowadzono analizę niestacjonarnych wymuszeń działających na łopatki wirnikowe w stopniu z upustem turbiny 13UC100. Niestacjonarne siły zostały wyznaczone dla 4 punktów pracy upustu. Wskazano na możliwą przyczynę zaistniałego zniszczenia łopatek wirnikowych turbiny.
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The community involvement of courts: an action research study in the context of the Polish justice system
PublikacjaPurpose – As a rule, common courts are hermetic organizations, separated from their stakeholders by procedures based on legal provisions. For these reasons, they are often perceived as unreliable and non-transparent, and as such, they do not inspire trust among stakeholders. The authors posit that the court’s community involvement may lead to the increased accountability and legitimacy of courts, which should in turn result in...
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Chain Action - How Do Countries Add Value Through Digital Government?
PublikacjaThis study examineshow countries develop and benefit from Digital Government(DG).The literature proposes various conceptualizations of the value-adding logic of DG, but the benchmarking practice is not respondingto such proposals.For instance, the United Nations’E-Government Surveycombines the readiness and uptake indicatorsand failsto cover any impactindicators;thus,its diagnostic valueis limited. To overcome...
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Study of pozzolanic action of ground waste expanded perlite by means of thermal methods
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublikacjaIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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How to achieve sustainability?-Employee's point of view on company's culture and CSR practice
PublikacjaThe people are the company. This study aims to examine the structure of relationships between company culture, performance, corporate social responsibility (CSR), and reputation, as seen from the employee's perspective, to determine which company culture factors most influence CSR practice and, as a result, sustain a company's development and improve its performance. To accomplish this goal, we conducted a survey among employees...
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Novel therapeutic compound acridine–retrotuftsin action on biological forms of melanoma and neuroblastoma
PublikacjaPURPOSE: As a continuation of our search for anticancer agents, we have synthesized a new acridine-retrotuftsin analog HClx9-[Arg(NO2)-Pro-Lys-Thr-OCH3]-1-nitroacridine (named ART) and have evaluated its activity against melanoma and neuroblastoma lines. Both tumors develop from cells (melanocytes, neurons) of neuroectodermal origin, and both are tumors with high heterogeneity and unsatisfactory susceptibility to chemotherapies....
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Analysing Ways to Achieve a New Urban Agenda-Based Sustainable Metropolitan Transport
PublikacjaThe New Urban Agenda (NUA) sets a new vision of sustainable urban development to help cities deal with the challenges of changing demography. While numerous articles have addressed how the NUA can be implemented at different levels and in different areas, this article points out the potential limitations in incorporating the NUA into metropolitan transport policies. The relevance of the limitations can be seen in three main fields:...
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Reactive extrusion of biodegradable aliphatic polyesters in the presence of free-radical-initiators: A review
PublikacjaNowadays, growing attention is being paid to the environment and sustainability, what fully justified research works focused on modification of biodegradable polymers and their composites. In this field of research reactive extrusion seems to be the most promising approach, which fits well to sustainable development strategy. In In the present work, the in-situ modification of biodegradable aliphatic polyesters and the compatibilization...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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A ROLE PLAYING GAME NAME GENERATOR LEARNING ITS CREATIVITY FROM ARKADIA MUD PLAYERS
PublikacjaThe paper proposes an approach to creative generation of new names for the purposes of Role Playing Games in fantasy realms. The generator based on an existing database of na mes is able to propose a set of new names with regard to demanded attributes, such as: length of the name, sex and race of the character, a given p hrase as the origin for the generated name as well as subjective evaluations from former users. The software...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Errorless Learning as a method of neuropsychological rehabilitation of individuals suffering from dementia in the course of Alzheimer’s disease
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Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublikacjaHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Implementing SP4CE Learning Rooms concept and AUTODESK online certification in the preparation of a new generation of engineers.
PublikacjaIn academia, educators do not always cope with rapidly changing technologies. Yet keeping up with new trends is essential to graduates’ success in a competitive job market. In the article, the author will answer the question of how Autodesk University Open Educational Resources and Certiport exams including GMetrix can enhance students’ academic progress and prepare them for future career. The concept of co-operation between Authorized...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublikacjaThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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Identyfikacja i izolacja genu kodującego zaadaptowaną do zimna β-galaktozydazę Paracoccus sp. = Identification and izolation of the gene encoding cold-active β-galactosidase from paracoccus sp.
PublikacjaZaprezentowane badania były prowadzone u eehi wyizolowania ze środo¬wiska organizmu psychrofilnego, zdolnego do hydrolizy laktozy w niskiej tempe¬raturze, oraz zidentyfikowania genu kodującego (i-galaktozydazę zaadaptowaną do zimna.Poszukiwan gen został w izolowany z psychrofilnego szczepu autarkicz¬nego Paracoccus sp. 321). Na podstawie sekwencji nukleotydowej genu kodują¬cego fS-galaktozdaze ustalono skład aminokwasów),...
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An MTA-phosphorylase gene discovered in the metagenomic library derived from Antarctic top soil during screening for lipolytic active clones confers strong pink fluorescence in the presence of rhodamine B.
PublikacjaIn this work, we present the construction of a metagenomic library in Escherichiacoli using the pUC19 vector and environmental DNA directly isolated fromAntarctic topsoil and screened for lipolytic enzymes. Unexpectedly, the screeningon agar supplemented with olive oil and rhodamine B revealed one unusual pinkfluorescent clone (PINKuv) out of 85 000 clones. This clone harbored a plasmid,pPINKuv, which has an insert of 8317 bp that...
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Synthesis and biological evaluation of 2,7-Dihydro-3H-dibenzo[de,h]cinnoli- ne-3,7-done derivatives a novel group of anticancer agents active on a multidrug resistance cell line.
PublikacjaZsyntezowano serię pochodnych pirydazonu z jednym lub dwoma łańcuchami bocznymi w różnych pozycjach chromoforu tetracyklicznego. Związki wykazały aktywność cytoksyczną na mysią białaczkę L1210 i ludzką k562 oraz na linii komórkowej oporności krzyżowej MDR (k562/DX). Dwa najbardziej aktywne związki przetestowano in vivo na mysiej białaczce P388. Wykazały one aktywność przeciwnowotworową porównywalną z aktywnością Mitoxantronu.
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Salinity enhances high optically active L-lactate production from co-fermentation of food waste and waste activated sludge: Unveiling the response of microbial community shift and functional profiling
PublikacjaLactic acid (LA), a versatile platform molecule, can be fermented from organic wastes, such as food waste and waste activated sludge. In this study, an efficient approach using salt, a component of food waste as an additive, was proposed to increase LA production. The LA productivity was increased at 10 g NaCl/L and optical pure L-lactate was obtained at 30 g NaCl/L. The enhancement of LA was in accordance with the increased solubilization...
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Thermal self-action effects for acoustic beams containing fronts in a Maxwell relaxing fluid
PublikacjaThis paper examines the thermal self-action of acoustic beams in a Maxwell relaxing fluid. This type of thermal self-action differs from that in a Newtonian fluid and behaves differently depending on a ratio of sound period and time of thermodynamic relaxation. The self-action which relates to sound beams containing shock fronts is also discussed. In addition, stationary and non-stationary types of self-action are considered.
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THE POSSIBILITIES OF ESTIMATING THE RELIABILITY OF SHIP PIPELINES’ ELEMENTS INCLUDING DESTRUCTIVE PHENOMENA ACTING ON THEM
PublikacjaIn the article an approach to the problem of estimating reliability data based on physical models is proposed. The possibility of reliability assessment for selected elements of ship pipelines, based on the recognition of the destructive physical phenomena taking place in them, is discussed. To do this, an overview of these phenomena has been made. In addition, a preliminary review of existing measures of destruction of materials...